Research digitisation will be the next advantage in the financial markets

Research digitisation – the process of applying technology to automate the discovery, collection and distribution of relevant financial information by an institution to its clients or internal team to increase efficiency.

How does a bank with multiple, disparate financial research documents across asset classes, sectors and geographies effectively organise and distribute that information to its maximum advantage?

Banks are now turning to research digitisation to gain significant advantage and improve client service

That’s potentially billions of individual pieces of useful financial information, spread across and deep within thousands of individual research documents. Potentially highly valuable information to the pre-trade decision making process but worthless unless in an organised workstream which can be collated and distributed within a bank or distributed to a client.

Market data heads, heads of research and analysts and their teams have the unenviable task of managing, make sense and distribute the key points from thousands of detailed, in-depth documents.

The golden goose is to create a financial research workflow so the best information on a given topic can distributed internally or to clients efficiently and accurately, minimising human error.

Financial research has been overlooked and underserviced by the tidal wave of technology looking to improve the efficiency and operation of markets. The trading process in particular has an embarrassment of riches in terms of investment and adoption of new offerings, models delivered through technology.

Research digitisation – the new advantage

Banks are now turning to research digitisation to gain significant advantage and improve client service as technology developed to turn financial research into the asset it was meant to be.

This new focus on research digitisation is not dissimilar to the massive push and focus markets had on mining and distributing historical market data.

There was a huge amount of investment and institutions really upped their game and invested to stay ahead. We’re now seeing a similar pattern with research. It’s a new front where banks can distinguish themselves and gain an advantage internally and for clients.

Accessing material in a detailed and practicable way transforms large research documents into targeted insights, powering financial activity and enhance business progress.

Research need to have intelligence and flexibility underpinned a global perspective with the ability to reach across the capital structure and all asset classes.

Traditional search processes such as looking through an email inbox or using a “Control+F” function in a text document makes it difficult to discover real insights. The inability to quickly gauge relevant material may lead to market participants missing out on valuable investment opportunities in financial markets.

Providing a detailed assessment of paragraphs and generate a 360-degree view of the subject is important in all market conditions.

This requires technology which tags every paragraph of each document in context, in real-time, transforming a body of research from a series of unstructured documents sitting in a digital library, into a huge matrix of tagged material. This works with specific words, synonyms and associated phrases.

For example, if you were looking for information on “the US-China trade war” you would have to search for a series of combinations involving multitude synonyms from “tariffs” to “US-Sino trade tensions” and then you would need to surface only those specific paragraphs relating to the relevant countries.

Document atomisation

This ability within research digitisation is called “document atomisation”. Essentially this unlocks the value buried deep within the research without requiring the analyst to change how they write or publish their articles.

Once the insights in the research have been atomised, they can be analysed and presented through an ecommerce platform, chat function or directly to a client or internal portfolio managers.

For example, if a bond trader is planning to buy German Bunds, their search would bring up the relevant paragraphs in a document on German GDP as well as useful sections of other articles on ten-year Bund yields. Other relevant paragraphs in documents dealing with the euro, or the latest German Purchasing Managers Index numbers, would also be surfaced.

Personalised atomisation of the information enables the trader to quickly read all the relevant paragraphs within their research library without having to sift through entire documents one-by-one, saving a considerable amount of time.

And because the reader is only seeing the relevant paragraphs, detailed and accurate metrics are supplied to the research report writer on what information within their output is most useful; this enables a refinement of research production in future.

The atomisation process enables unstructured information to be transformed into structured intelligence, capable of being analysed by both humans and computers, and communicated via application programming interfaces (APIs) and is the key to delivering research digitisation at an institutional level.

Research digitisation, underpinned by developments in artificial intelligence (AI) and rich natural language processing (NLP) and intuitive workflow tools, is a source of genuine competitive advantage with applications reaching far beyond financial markets.

The use of data will also change – both how we use it to generate content and how our clients consume content.

For now, the banks and funds are once again the first movers, investing in this smart technology to transform the information overload of financial research, from a liability into the valuable asset it is intended to be.